Automate your Data Mesh implementation

Data Mesh empowers data domain teams by placing the responsibility of implementation squarely on their shoulders. Datavault Builder is an invaluable tool for these teams, enabling them to quickly deliver data products to their customers in a format that’s both understandable and maintainable.

With Datavault Builder’s multi-tenant capabilities, every data domain team can operate in its own independent environment, following their unique release schedules.

Business Model Driven

Beginning with the business model allows for early involvement of data product consumers, ensuring the output is comprehensible post-implementation.

The integration of diverse data sources enriches data products, delivering substantial business value.

Covering the Full Processing Chain

Datavault Builder handles the full spectrum of data integration, including historization and harmonization, managing all your documentation and governance needs in the process.

Automatic Data Lineage

A crucial aspect of Data Mesh implementation is self-generating documentation that remains current. Datavault Builder automatically derives all necessary documentation from the generated code, keeping everything synchronously updated – at all times.

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How to Automate Data Mesh

Explore our live demo to discover how to create and combine data products across different data domains.

About Data Mesh

Data Mesh is a data governance framework designed to optimize data usage within an organization. It fosters a shared understanding of data among all stakeholders and advocates for decentralized ownership and control of data assets. By encouraging the development of a mesh of data products, each managed by a cross-functional team responsible for its complete lifecycle, Data Mesh aims to establish a decentralized data governance model. This model enables teams to independently find, understand, and utilize data, reducing dependency on centralized data management teams or processes. Such an approach aids organizations in becoming more agile and responsive to business shifts, enhancing their ability to leverage data assets for a competitive edge.

Key Principles of Data Mesh:

Decentralized Ownership and Control of Data: Teams manage the entire lifecycle of their data, from discovery to usage.

Shared Understanding of Data: Common data definitions and vocabularies promote a universal understanding of data across the organization.

Data as a Product: Data is seen as a product managed by a team, not as a shared resource under centralized control.

Continuous Improvement: Feedback loops and agile processes encourage ongoing enhancement of data products’ quality and value.

Adhering to these principles, Data Mesh can significantly enhance an organization’s capacity to leverage its data assets, boost data quality and trust, and increase its agility and responsiveness to new business challenges.

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